Natural Language Processing - Sarcasm Detection
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Updated
Feb 14, 2017 - Java
Natural Language Processing - Sarcasm Detection
To predict future stock prices by influence of Opinion mining using Deep Learning techniques
Naive-Bayes classifier to classify hotel reviews as part of CSCI 544 - Applied Natural Language Processing Course
Development of an Public Opinion Mining System as part of my Bachelors Thesis
Analyze sentiment and mine opinions é uma solução da plataforma Language Studio, da Azure, que permite detectar sentimentos positivos, negativos e neutros a partir de sentenças. Esse repositório mostra alguns exemplos de testes na plataforma. Os procedimentos foram realizados como parte do Bootcamp Microsoft Azure AI Fundamentals, da DIO.
Sentiment (tonality) and opinion mining analysis in Russian texts / Определение тональности и выделение высказываний в тексте на русском языке - Демо
Exploiting Behavioral Features to Detect Fake Reviews by Means of Contextual Features
Copenhacks 2018 code for Crowdinator. Crowdinator is a sentiment analysis tool that detects the emotion of a crowd using face analysis from a given stream of images and generates a visual report.
Script di Opinion Mining realizzati per la Tesi di Laurea in Informatica e Tecnologie per la Produzione del Software: "Estensione di un Recommender System Conversazionale Mediante Tecniche di Opinion Mining".
[ACL 22] Identifying Chinese Opinion Expressions with Extremely-Noisy Crowdsourcing Annotations
Testbench for sentiment and factuality in texts.
Sistemi Intelligenti per Internet - Università Degli Studi Roma 3
[NLP] Analysis of reviews from mobile apps related to air quality
Results of analyzing twitter opinion-mined e-commerce data.
Opinion Mining - Hybrid Approach
Sentimental Analysis using Machine learning models in R.
Text Mining Project @ NOVA IMS Authors: António Cymbron | Duarte Redinha | Maria João Marques | Lisbon, Portugal | June 2022.
Tugas akhir (final year project). This source code was used in the bachelor thesis “Public Sentiment Analysis of Mental Disorder based on Twitter Texts using Support Vector Machine”.
A place where opinions are experimented!
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